data collection

Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.

How are you balancing strong security and the customer experience? The European Union’s General Data Protection Regulation (GDPR) requirement is an opportunity to properly balance privacy and the user experience. Those who embrace it will distinguish themselves as a trustworthy and respectful custodian of their users’ data. Personal data plays an increasingly important part in providing the kind of appealing experience that brings users back time and time again. But, there’s a balance to be struck. Strong security is the best tool available for navigating the dichotomy between an appealing user experience and the risk posed by data breach; it allows the collection and management of personal data in line with the user’s expectations, and without jeopardizing the trust that is so important between them and you.

As IT becomes the cloud, and ever more central to business success, projects to transform the IT systems, and more specifically the data center, have become strategic and a competitive differentiator. A crucial piece of the data center transformation puzzle, and one which is too often left until the end, is the network. As the central nervous system of the data center, its transformation must be an integral part of the entire data center transformation project.

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Supporting multiple internal clients and all of their requirements for testing and production networks in more than 1,000 cities around the world—these are the unrelenting challenges for the 12 brands that comprise eBay Classifieds Group. Activating new platforms and features can take a lot of time; with the Juniper solution, turnaround time has been reduced to a few hours—sometimes less—which helps eBay Classifieds turn innovation into a real competitive advantage every single day.

The broad adoption of the next generation of cloud, mobile, M2M, and big data applications is having profound impacts on IT and network infrastructures. Compared to traditional applications, these applications have much shorter life cycles. You must be able to spin them up, spin them down, and grow and shrink them on demand. Furthermore, you must be able to move these application workloads within a data center or across geographically distributed data centers, resulting in increased management complexities.

The primary purpose of containerized applications is to improve the effectiveness of software teams, making it easier for people to work together while lowering the communications overhead. In large enterprises, applications such as ERP or CRM software suites often begin as simple projects, but as time passes, they quickly become clunky and inefficient, with a monolithic code base that slows progress for development teams.

eBay Classifieds supports multiple internal clients and all of their requirements in more than 1,000 cities around the world. The company adopts cloud and virtualization services to get to market faster with new features, services, and campaigns using Juniper Networks Contrail Networking, Contrail Cloud Platform and QFX5100 Switch.

After rapid expansion of vendors and features, players in the operational DBMS market continue converging toward feature parity. Data and analytics leaders will be interested in the lack of Visionaries, competition in the Challengers quadrant and the maturing cloud capabilities among these vendors.

To maximize the benefits of its next-generation systems and successfully execute its information strategy, CU had to overcome its aging network. Most of CU’s network infrastructure, which was built from solutions by another vendor, was introduced in 2007, when its computing center was first built. Over time, the equipment began to fail, affecting the stability of applications which relied on network connectivity. Technical support also became a major issue as the equipment faced obsolescence and maintenance contracts with vendors expired.

As flash costs continue to drop and new, flash-driven designs help to magnify the compelling economic advantages AFAs offer relative to HDD-based designs, mainstream adoption of AFAs —first for primary storage workloads and then ultimately for secondary storage workloads — will accelerate. Well-designed AFAs that still leverage legacy interfaces like SAS will be able to meet many performance requirements over the next year or two.
Those IT organisations that aim to best position themselves to handle future growth will want to look at next-generation AFA offerings, as the future is no longer flash-optimised architectures (implying that HDD design tenets had to be optimised around) —
it is flash-driven architectures.

Cloud computing and all-flash storage are two of the most important innovations driving next-generation IT initiatives. While it may seem at first that these are parallel trends, in reality they are inextricably intertwined. Without the benefits of all-flash storage —driving new levels of performance, agility and management simplicity — enterprises would not be able to modernize their infrastructures to deliver cloud services. It is no coincidence that the largest hyperscale cloud providers rely on all-flash storage solutions as their storage foundation.
Pure Storage all-flash storage arrays provide enterprise customers with a safe, secure and smooth path to the all-flash cloud. You can take the journey in stages, starting small with a single application or two, and then adding more applications through consolidation and virtualization. You can also implement multiple stages at once.

Storing data is critical. Everyone stores data. Today, it’s all about how you use the data you’re storing and if you’re storing the right data. The right mix of data and the ability to analyze it against all data types is driving markets worldwide in what is known as digital transformation.
Digital transformation requires storing, accessing, and analyzing all types of data as fast and efficiently as possible. The end goal is to derive insights and gain a competitive advantage by using those insights to move faster and deliver smarter products and services than your competition.

The growing need for organizations to treat information as an asset is making metadata management strategic, driving significant growth for metadata management solutions. We evaluate nine vendors to help data and analytics leaders find the solution that best suits the needs of their organization.

Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems.
Data Lakes are a new and increasingly popular way to store and analyse data that addresses many of these challenges. Data Lakes allow an organization to store all of their data, structured and unstructured, in one, centralized repository.

Financial reporting teams, often led by Controllers, face mounting pressure to provide accurate, useful, and timely data, while also decreasing turnaround time and costs. Regulatory agencies don’t care if an organization is short of staff or if its financial management system amounts to a collection of spreadsheets.